I did a little digging in Google Groups, and I was a bit stunned by what I found. My first post in comp.lang.python (although I was using the python-list@cwi.nl at the time) was about emacs and used regular expressions:
I just whipped up this code to make hilit19 deal w/ python code relatively properly. Put it in your .emacs file.
Note: detecting documentation (e.g. triple quote strings after class or function definitions) as comments rather than strings would be nice, if anyone is motivated enough...
So, here we are, 11 years later, and I'm still writing code to make better tools for hacking Python. Depressing in a way, but we won't dwell on that. (This post is even scarier!)
Instead, let's go a little bit earlier, a few months earlier in fact, because what led me to Python is maybe more important than my particular obsession within it. I was a grad student doing work in auditory research. Like a lot of grad students, what I was actually doing was writing C++ code and then trying to get my fellow grad students to appreciate the beauty of my code. It became pretty quickly clear that that wasn't going to happen with C++ code, so I figured I would write a scripting front-end. As a victim of a compiler class, I grabbed my copy of the Dragon book, and started defining a grammar, fighting the parser generator, and got really, really frustrated. After too many days of pain, I realized that I wasn't in a class, and that what really mattered was getting a scripting front-end, not being the one to invent is. I did a little altavisting (somehow doesn't work as well as Googling', but those where the days), and came across two languages: Phantom and Python. (Phantom didn't grab me, go wonder). I don't know why I didn't think of using Tcl and Perl, two languages I already knew. Anyway, I quickly downloaded the tutorial, read it, and was immediately quite excited (my officemate was then quickly subjected to long raves about this language which "was even cooler than MetaPost", which was my newest toy at the time).
I quickly got involved on the newsgroup, threw out ideas, and got answers from Really Nice Folks. People were just so incredibly encouraging, from Guido ("ooh, Guido wrote to me!") to Tim Peters, to /F (back then he was more cheerful =), Uncle Timmy, Don Beaudry, Ken Manheimer, Barry Warsaw, and lots more. I will always be very grateful to them all. It's truly amazing how much fun was had by all over so many yerars. The conferences were very important, but the mailing list is what kept people involved every day for years, long before anyone was making any money with the stuff.
I'm extremely lucky that for me it became more than fun, as it slowly turned into a job, a book, another job, another book, yet another job.
The world would be a much better place if everyone could experience this kind of long-term involvement in activities that combine intellectual curiosity, learning, fun, and real friendships. It's hard to recall the last 11 years and not think that the internet is so damn cool, that programming is fun, and that there are a lot of nice people out there.
In 1996 funny enough it was Perl I didn't know at all which brought me to learning Python. Having bought a Perl O'Reilly book I realised after one week that it was about Perl 1.4 but not the new version Perl 1.5. I returned it to the book store and asked to order the new one. I looked around and discovered under another copy of that Perl book "Das Python Buch" published by Addison-Wesley. I browsed through it and fell immidiately in love with that language whose syntax looked much more familiary to me than the Unix script based language Perl. Fortunately it was easy to read and understand during the 10 minutes bus drives in the morning. No surprise I sticked with Python until today.
In the beginning I was promoting Python for our work. There was a strong opposition against Python - We use TCL and Perl but nobody uses Python - Most of our scripts are Perl - Python is inferior to Perl and so on. After I gave up and used Python only for my own problem solvings more and more people in other departments began programming in Python. I helped another collegue how to solve his communicating problems with an embedded controller. He restraining using Python years ago is now so enthusiastic that even his 10 year old son got "Python for Kids" as a Christmas present. His Python programs are also reaching some other departments of our company.
Just recently - Python hit our group!!! Our system administrator substituted his commercial family tree program with a Python equivalent. This was enough reason for him to learn Python. After some time he prefered writing our scripts in Python instead of Perl. Recently we rewrote one of his Perl programs relying heavily on external Unix commands completely in Python - cutting its execution time from tree minutes to five seconds. Recently working in a mixed Sun/Solaris and Intel/Redhat environment some of the old scripts show ugly errors which can be easily avoided with rewriting them in pure Python. Also my collegues ask our Sysop for help with their problems. He shows how to solve them in Python - and they are starting reading Python books as well.
In the end - 10 years after my Python promotion - Python is settling in our group. Collegues outside my group are using Python for years now - we are the last. It is not exactly a success story for me.
I started with Python in 1998. I am not sure that makes me an old-timer. I'm one of those people that should have started 5 years earlier and the huge complicated project I had been working on in C++ might have succeeded.
I came to Python as a way to prototype some GUIs for a medical workstation, and learned it from example and reading the manual. By that time, it was too late and the project as a whole had pretty much failed. But boy was I blown away with the productivity and clarity of code when working in Python. I was looking to move on anyway, so I took my enthusiam for Python and co-founded Wingware (makers of a commercial Python IDE).
> I helped another collegue how to solve his > communicating problems with an embedded controller. He > restraining using Python years ago is now so enthusiastic > that even his 10 year old son got "Python for Kids" as a > Christmas present.
It sounds like you may be referring to "Mit Python Programmieren für Kids" by Georg Lingl (ISBN: 3826609514).
I I'm not sure my kids could cope with simultaneously learning Python and German in one hit, so there could be a nice (very) little earner for someone willing to port the book to English.
Thinking about it; With some decent artwork and a lively written style ("Head First Programming for Kids (using Python)" perhaps?) the opportunity exists to create an audience for whom Python is their first programming language - and consequently their language of choice in the future.
V.
(PS. As a ten year old kid, I'm sure I would have preferred a new bicycle but that's another story.)
I discovered Python in 1995 and have been using it ever since as my main programming language.
Back then, I was starting to work on biomolecular simulations, using a package well-known in the field that was a pain to use and a nightmare to modify: large amounts of Fortran code written by dozens of graduate students who had been learning Fortran programming on the job. I was spending way more time analyzing badly written code than working on my own project.
Since I expected to stay in biomolecular simulations for a while (I still do), I started to look around for better tools. Unfortunately, there was no package that had the functionality I needed and the quality of code that I expected. I decided to write my own. I knew that to do in a few years alone what groups of dozens of people had done in two decades, I had to be a lot more efficient. I also knew that both C and Fortran, the two languages I was fluent in at the time, were too low-level for the task.
I began a systematic exploration of programming languages as a side project. Some candidates were eliminated quickly (e.g. Lisp for its overdose of parentheses, and Smalltalk for its bad integration with the world of file systems), others were examined more seriously by using them in a small programming project: C++, Perl, and Python. Python convinced me immediately: clean syntax, a clean object model, a good C interface, a rich standard library, and a community of smart and helpful people. The Numerical Python project, in which I was involved from the start, removed another barrier to the use of Python in scientific computing.
Since then, I have written a large amount of scientific computing code in Python, using just as much C as strictly necessary. Most of my code is contained in two libraries that I distribute as Open Source code: ScientificPython (http://dirac.cnrs-orleans.fr/ScientificPython/) and MMTK (http://dirac.cnrs-orleans.fr/MMTK/).
Back in 1995, using Python for scientific computing required a good bit of courage. Most of my colleagues just didn't take Python serious, and even the more open-minded ones considered the idea of using an interpreted language an obvious stupidity. In the 11 years that followed, the situation has changed for the better: scientists and engineers are starting to use Python now everywhere around me, and I am invited regularly to teach Python classes for scientists or to present my packages written in Python.
Not a Python old-timer really... started in early 1997 with 1.4 at Four11.com where we developed Yahoo!Mail (called RocketMail back then... anyone remember that or still have an acct?).
We used Python and C++ plus our own home-brewed templating system well before such things existed... the closest I guess would be Cheetah. I haven't made any real serious patches to the source, just various bugfixes and enhancements over the years.
Back then, the only Python books available were Aaron Watters "Internet Programming with Python" and Mark Lutz's "Programming Python". I picked up most of my Python from the Library Reference, and with the development of Python training courses and the aging of those books, I was highly motivated to write "Core Python Programming" (http://corepython.com).
My how Python has changed since then. We've come full circle as 2nd ed is coming in a few months! I look forward to another session of reminiscing when Python is 2 ** 5 years old.
I'm actually more of a "medium-timer", having used Python for less than 10 years.
My first exposure to Python came when I was working in Tokyo at a small company doing SGML data processing, specializing in East Asian languages (Japanese, Chinese, Korean). It was a high-stress but fun environment, where the work always had to be done *yesterday*. We'd write code and run it on (usually buggy) client data, and debug the system until it ran correctly, then the job was done. There were a lot of one-off programs, but not insignificant. A typical day saw me coding in Scheme, PostScript, shell, and Perl. Lots of Perl. From single-line filters to a multi-thousand-line program that parsed ASCII-art syntax diagrams, I was immersed in Perl for over 2 years. By the end, I was sick of Perl; it just didn't scale, and maintenance was a nightmare.
Toward the end of my stay in Japan, probably in 1997, a colleague picked up a copy of the first (1996) edition of "Programming Python" by Mark Lutz and was impressed. I took a look and liked what I saw, but was so busy that I didn't have time to get into it then. I moved back to Canada in 1998 with my wife and infant son, took some time off, picked up my own copy of "Programming Python", and delved deep. I really liked what I saw, and started a Python rewrite of a project I'd written in university in Pascal (a Pentominoes puzzle solver) to learn the language. I got it working well enough -- it was slow and buggy, but the project had served its purpose: I was now comfortable coding in Python.
The code flowed. Maintenance was a breeze. I found myself writing code that, except for the odd syntax error or typo, would often *just work*, first time. As the saying goes, Python fits my brain. I was able to tackle large projects much more easily than ever before. And thanks to Python, programming became fun again.
While learning the language I discovered docstrings and started looking around for autodocumentation systems to exploit them. The choices available then weren't exactly what I was looking for. It seemed that many people had tried their hand at autodocumentation, but nobody had produced anything sufficiently generic for my liking. Either the source code was imported (where I wanted it to be parsed), or the output was fixed (it should be flexible), or the markup was either deficient or cryptic and hard to read (it should be rich, yet implicit and easy to read). I foolishly took on this task, and eventually focused on the last aspect: the markup. Docutils & reStructuredText were born, and the rest is history (http://docutils.sf.net/docs/ref/rst/introduction.html#history).
I have contributed several small fixes and enhancements to Python's standard library, I occasionally participate in Python-Dev discussions, but my most significant community role (apart from Docutils) is probably as Python Enhancement Proposal (PEP) editor. I have also been involved with organizing PyCon, and have attended for three years running. I became a nominated member of the Python Software Foundation in 2003, and have been active with the Board of Directors, becoming an officer (Assistant Secretary in 2005 and Secretary this year), and I was elected as a director in February 2006.
I now program almost exclusively in Python. I recently revisited my Pentominoes solver, using a different approach, which works very well. Docutils still doesn't do Python autodocumentation natively though. Other autodocumentation systems use Docutils, but the "ultimate solution" has yet to be written. One of these days...
I first looked at Python in 1993 during I made a trip to France to see my later-wife. This was only my third time seeing her and I showed up with this monstrosity of a 286 laptop and pitched tent in her kitchen going through the Python tutorial. Nearly every one of my flaws was there for her to see, early on.
At that time I was working on www.navy.mil and the idea of CGI was starting to come out. I wasn't much of a programmer: anything important I've ever written was immediately rewritten by someone talented. I remember looking at the Perl book and thinking, "Only if I have to." The Python tutorial is what pulled me in.
I went to the first Python "conference" organized by Michael McLay at NIST. Though I didn't have much to contribute, I really enjoyed it. After that I got involved with efforts at a foundation, then got involved in the next few Python conferences. Rob Page and I started a company that created a platform for newspapers to publish online. Jim Fulton, who organized the second and perhaps third conferences and did a bunch of core Python stuff at the time, joined us and we got heavily involved in Python.
I'd say that nearly everything I know about groups of people working together online for a common purpose comes originally from the Python community. This thread was a nostalgic celebration with tons of evocative memories from years past. Now that I'm moving back to the US and re-joining the PSF, I hope I get to PyCons and can catch up with some friends from years past.
Thanks Guido for starting this thread and Michael for nudging me to post.
Well, my first post to comp.lang.python was in mid April 1995.
thinking back to then, I would have had one of a series of Acorn Computers at home, and would have been using Sun workstations at work. I would have been programming in AWK, C, and Cadence Skill; and would have been scouting around for a language to replace AWK, that ws NOT Perl, (Perl and I do not gell - although i have had to do a fair amount of Perl programming over the years). I wouldn't have done much with Python except admire it as I remember it took some time before it was ported to the Acorn platform.
We have been using Python in the Space Shuttle program since 1993 when I first downloaded it from the CWI in Amsterdam. At the time there was a project to re-develop our fundamental trajectory simulation capabilities as a library of reusable components. We needed a language which could be used as an executive, or control, mechanism for all these C++ classes we were developing. The web was very young then, (I think there were only a few hundred HTTP servers in the world then), but I was able to use gopher to search for "Object Oriented Programming". Behold this thing called Python popped up and I went to the URL. From CWI I downloaded I think version 0.93 and untarr'ed the source. It built without trouble on our Sun workstations in a few minutes. (I was impressed already.) We soon realized we had the perfect tool for the job. Python could bind to C/C++ libraries easily with its API, and its object oriented syntax matched the C++ objects we were writing object for object, method for method. I was a Perl user too and Python put an end to that! We've been enthusiatic Python boosters (sic) ever since. I was even able to talk my company into sending me up to Gathersburg to the first Python Workshop. Can't say that I've contributed anything to the Python language but boy have I been exploiting it!
I've been using Python on-and-off since 1992. I remember stumbling upon one of Guido's postings in comp.lang.tcl; at the time, we were using Tcl for a virtual reality project at the University of Virginia.
It wasn't long before we switched to Python (I think it was still version 0.7 in those days.) Needless to say, we never looked back. The perfect word to describe Python then and now is "elegant."
Oddly enough, 14 years later, I work with one of my fellow researchers from UVa, and we still talk about Python.
My fondest memory in demonstrating the power of Python was a project called "Dancer", a small graphical web browser that used Tk. It only took about two days to write - granted, it wasn't Mosaic, but not many other languages let you prototype that fast, even today.
Twelve years ago CNRI co-worker Barry Warsaw had discovered Python through friends Michael McLay and Ken Manheimer. He and I attended the first Python conference, along with eighteen others, held at the National Institutes of Standards and Technology (NIST) in December 1994. The author of Python mediated the conference, a Dutchman named Guido van Rossum. We were impressed with the technical merits of his small object-oriented scripting language but even more so with its inventor.
Even though Barry and I were focused on using Objective-C and the NEXTSTEP environment as our main programming tool, we had a requirement for a scripting language for a project that implemented code mobility [Knowbots]. Knowbot programs were running programs that package up their state, and migrated to a new machine resuming operation at the new location. For this effort, we were in search of a language that was interpreted but at the same time had all of the capabilities of the most powerful compiled languages. We considered other interpretive languages and drew the following conclusions:
1. Perl is a powerful scripting language that grew out of the UNIX system administrator community. It has powerful regular expressions and excels in parsing system logs when searching for particular items. We felt that Perl’s syntax was overly complicated. This made for difficult program readability and maintainability. Another problem was as the time of the evaluation Perl5 had just be introduced and was not as robust enough to be in consideration. Perl4 lacked any object-oriented features and, because of its nearly non-existent extension mechanism, was very hard to extend. Despite showing impressive runtime performance, our evaluation of Perl concluded that it was not ideal. Because of the syntax complexity issues, it would be difficult to teach Perl to new users particularly if they were not already programmers. We were in search of a simpler language with the power of Perl.
2. Tcl was considered because of its simplicity despite having strange syntactic qualities. With Tcl, we feared that large programs would be difficult to maintain. In the final analysis, we rejected Tcl because it lacked performance, any numeric data-types, intermediate compilation, and object orientation. We were in search of a language of simplicity, but not at the expense of expressiveness, scalability and power.
3. Java is an interpreted environment similar to that of Python. "Compiled" Java programs are executed by the Java Virtual Machine. The Python interpreter executes Python programs after compiling Python source code to Python byte-code. With the exception of differing byte-code formats and the existence of Just-In-Time (JIT) compilers for some Java Virtual Machines (JVM), Java and Python have somewhat similar execution environments. Despite the fact that at the time of our evaluation, Java was still a research effort, Java was the only other real consideration for our code mobility project. Java had powerful expressiveness, object-orientation, a full suite of data types, and a platform independent byte-code representation (a valuable feature for implementing code mobility). In the end we decided that Java, was not for scripting. It possesses the same lack of very-high-level-language quality as C++ and Objective-C. We found Java programs to be two to three times as many lines-of-code as the Python equivalent.
At the end of the two-day conference we were nearly convinced Python should be our mobile code implementation language for our code mobility project. We were still planning on developing most of the supporting code using NEXTSTEP and Objective-C.
CNRI hired Mr. van Rossum six months later (score!) and with him we began to inherit his responsibilities towards promoting his language. As we became more familiar with Python and comfortable with its capabilities, we found ourselves using it to test varies theories and to prototype various ideas. The final prototypes could then be re-written in Objective-C or perhaps Java. After many months of using Python as a prototyping tool, we found, to our surprise, that there was little need to choose a different language environment to re-implement anything! This realization came around the same time we accepted the fact that our previous strategy for success was based too heavily on the strategy of a commercial vendor. Because NeXT computer was the primary source of Objective-C development environments and Sun Microsystems the controllers of Java, we were confined to their marketing directions and decisions based on commercial interests. We did not like having our technology choices made for us. This final straw allowed us a greater appreciation for Python's free status and liberal licensing.
Our initial evaluation of Python was as a scripting language for a specific part of a specific project. Our eventual adoption of Python was as a general-purpose language that became the tool of first choice.
That was twelve years ago. I'm happy to say that I'm still paid to develop software and software to develop software in Python.
The CNRI knowbots project ended up being the first of many Python projects at CNRI that paid the salaries of more-than-a-few Python luminaries (and some ..err not so luminary... like me):
Anton Benard David Binger Fred L. Drake Jr. Jeremy Hylton Jim Hugunin A. M. Kuchling Roger Masse Ed Overly Guido van Rossum Neil Schemenauer Greg Ward Barry Warsaw
Even though only David and I remain, we've been able to release much open-source software (see: www.mems-exchange.org/software) thanks to momentum we've carried by riding on the shoulders of several of the aforementioned giants and through the generosity of my employer. I almost never have to use other languages. Life is good!
I was introduced to Python first probably halfway 1994, by a colleague at EMBL Heidelberg, Michael Scharf. At some point he had given a course to group members called "object oriented programming using ET++", and a little after he had discovered python he repeated the same course but reworked into "object oriented programming using python". The course attendeed were each working on different tools to work on protein and DNA sequences, and at the end of the course there were many tools that, due to the well designed framework, worked seamlessly together to perform all kinds of analysis on the most varied set of sequence databases imaginable.
I was grepped immediately by the beauty of the result and the first proper explanation I got of object oriented programming; the first time the concept started to make sense to me after reading several books.
I have been a power user of FORTRAN, a heavy user of Tcl/Tk and a moderately hacky perl user before this time, but in the beginning of 1996 I really started my first serious projects in python and dropped all other scripting languages. February 1996 is also the first time I have posted on c.l.py. The biggest difference I felt between Tcl/Tk and Perl on one side, and Python on the other, is that python really invited me to properly reuse code I had written before. Reuse rather than copy and modify.
Then, in September 1997 I was employed by a company making X-ray analytical instrumentation in The Netherlands. They asked me to write their new application software suite in a forward looking way. I was allowed to do everything from scratch. The first time we talked about the project the company proposed to do it in Java, but I managed to convince people that python was going to be a better choice. In 3.5 years of one-man work the package did grow to about 75k lines of python and 1k lines of C. It used Tk/Pmw for GUI, and Numeric for computation. The package was unix only.
In April 2001 our company merged with the biggest competition. The newly formed conglomerate decided that all of the unix only programs from one side, and all of the windows only programs from the other, had to be merged into one cross-platform suite. This is the package that we are still working on, now with a handful of developers. It is still written for 95% in python and the rest in C++ (using boost-python) about 5x the size of the first generation tool, now with a gui in PyQt and still using Numeric. And it still contains some of the same concepts I learned in that first introductory course in object oriented programming!
It must have been the summer 1996. Back from a business trip to US' east coast, I came across a mentioning of Python on the Internet, maybe in an online magazine, someone saying Python is nice and cool, with a few pointers. I looked around and got caught by a nice, colour-full and easy-to-read article by David Asher (with lots of little pythons ;) that intrigued me. I installed Python 1.4 on a Windows 3.11 machine, and although being an old Unix horse, Python on Windows was my playground for quite a while.
Ahh, the syntax, a sight for sore eyes! (I was also making inroads into Perl at that time...). I read about Guido's Christmas project. Then I bought Mark Lutz' book, with another working-from-home story.
1997 I started my first Java project, with 5-day course and all. I had to design and implement a Java API for a network based service, but after a couple of weeks I got so fed up. Java kept getting in the way. Class designs had to be re-worked, interfaces be revamped. I spent increasingly time fixing class-cast exceptions. Meanwhile, colleagues were waiting to see code using my API, to review the design.
I did the client (API-using) code in Python, not daring to mention its name, calling it "pseudo code". It was clear, easy to read, and conveyed immediately how the API was to be used. Martin von Loewis' Python book was my every-day reference.
Then, when feedback came in, I put away with Java altogether. I implemented all classes in Python, re-worked them, revamped them, got more feedback, published more client code, did more API refinement. When the whole thing was settled, and everybody seems confident with the API, I simply re-implemented the Python classes in Java. SMOP. Done.
At home, Mark Hammond's PythonWin continued to delight me. A beautiful language with a free Windows IDE! It felt like Christmas every day.
On the job, Perl was establishing itself. Colleagues were trained, books were bought, old shell scripts were re-done in Perl. Hard to come up with another language. Hard arguments were needed. Those came up, when need arose to do some scripts on Windows using COM. Python's COM interface was more stable and mature than Perl's at that time (1999/2000), again most probably due to Mark Hammond.
Perl 1986, Python 1989. Often I thought, if only Python had been these few years earlier! We might all be doing Python by now...
Me & my friend (he works on Linux kernel these days for money), started looking at this thing called Python and open source in 2001. I think it was fairly new in India, REC-Trichy and our engineering college. We got some copies of python on the local RedHat linux machine and it was rage. We had a server where our LUG members used to post snippets, and other cool python scripts.
Personally my coming of age to python was learning to do a network programming script with implementing a FTP client. Doing stuff like networking in C is pain. Python you can just juggle around these things at your own cool time without worrying much about the socket.h
We were hooked! -Muthu
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